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CSC2515-University of Toronto. This project applied computer vision and mechine learning methods aimed to detect abnormal behaved object in crowd, by Hanwen Liang and Haohan Li.
abnormal behavior detection using CNN and RNN
Abnormal Human Behaviors Detection/ Road Accident Detection From Surveillance Videos/ Real-World Anomaly Detection in Surveillance Videos
Public places like restaurants and certain other viable places like banks or ATMβs are in need of constant supervision against amoral and undesirable activities. These undesirable activites are often markedly preceded by apparent behavioral quirks. However, constant manual monitoring using security cameras may miss abnormal cues preceeding unpleasant consequences due to human error. Picking up these quirks can improve the efficiency of monitoring any public place.This project attempts to semi-automize the security system using machine learning and image processing techniques to increase the efficacy and accuracy in the prediction of abnormal behaviour.
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